org.codelibs.elasticsearch.taste.similarity.TanimotoCoefficientSimilarity Maven / Gradle / Ivy

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/**
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.codelibs.elasticsearch.taste.similarity;

import java.util.Collection;

import org.codelibs.elasticsearch.taste.common.FastIDSet;
import org.codelibs.elasticsearch.taste.common.RefreshHelper;
import org.codelibs.elasticsearch.taste.common.Refreshable;
import org.codelibs.elasticsearch.taste.model.DataModel;

/**
 * 
 * An implementation of a "similarity" based on the 
 * Tanimoto coefficient, or extended Jaccard
 * coefficient.
 * 
 *
 * 
 * This is intended for "binary" data sets where a user either expresses a generic "yes" preference for an
 * item or has no preference. The actual preference values do not matter here, only their presence or absence.
 * 
 *
 * 
 * The value returned is in [0,1].
 * 
 */
public final class TanimotoCoefficientSimilarity extends AbstractItemSimilarity
        implements UserSimilarity {

    public TanimotoCoefficientSimilarity(final DataModel dataModel) {
        super(dataModel);
    }

    /**
     * @throws UnsupportedOperationException
     */
    @Override
    public void setPreferenceInferrer(final PreferenceInferrer inferrer) {
        throw new UnsupportedOperationException();
    }

    @Override
    public double userSimilarity(final long userID1, final long userID2) {

        final DataModel dataModel = getDataModel();
        final FastIDSet xPrefs = dataModel.getItemIDsFromUser(userID1);
        final FastIDSet yPrefs = dataModel.getItemIDsFromUser(userID2);

        final int xPrefsSize = xPrefs.size();
        final int yPrefsSize = yPrefs.size();
        if (xPrefsSize == 0 && yPrefsSize == 0) {
            return Double.NaN;
        }
        if (xPrefsSize == 0 || yPrefsSize == 0) {
            return 0.0;
        }

        final int intersectionSize = xPrefsSize < yPrefsSize ? yPrefs
                .intersectionSize(xPrefs) : xPrefs.intersectionSize(yPrefs);
        if (intersectionSize == 0) {
            return Double.NaN;
        }

        final int unionSize = xPrefsSize + yPrefsSize - intersectionSize;

        return (double) intersectionSize / (double) unionSize;
    }

    @Override
    public double itemSimilarity(final long itemID1, final long itemID2) {
        final int preferring1 = getDataModel().getNumUsersWithPreferenceFor(
                itemID1);
        return doItemSimilarity(itemID1, itemID2, preferring1);
    }

    @Override
    public double[] itemSimilarities(final long itemID1, final long[] itemID2s) {
        final int preferring1 = getDataModel().getNumUsersWithPreferenceFor(
                itemID1);
        final int length = itemID2s.length;
        final double[] result = new double[length];
        for (int i = 0; i < length; i++) {
            result[i] = doItemSimilarity(itemID1, itemID2s[i], preferring1);
        }
        return result;
    }

    private double doItemSimilarity(final long itemID1, final long itemID2,
            final int preferring1) {
        final DataModel dataModel = getDataModel();
        final int preferring1and2 = dataModel.getNumUsersWithPreferenceFor(
                itemID1, itemID2);
        if (preferring1and2 == 0) {
            return Double.NaN;
        }
        final int preferring2 = dataModel.getNumUsersWithPreferenceFor(itemID2);
        return (double) preferring1and2
                / (double) (preferring1 + preferring2 - preferring1and2);
    }

    @Override
    public void refresh(Collection alreadyRefreshed) {
        alreadyRefreshed = RefreshHelper.buildRefreshed(alreadyRefreshed);
        RefreshHelper.maybeRefresh(alreadyRefreshed, getDataModel());
    }

    @Override
    public String toString() {
        return "TanimotoCoefficientSimilarity[dataModel:" + getDataModel()
                + ']';
    }

}